Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Hardware
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

Ruzarh
/
c0ldv_T2V_Sigmoid_Flow_Rank64-lora

Text-to-Video
Diffusers
lora
template:sd-lora
ai-toolkit
Model card Files Files and versions
xet
Community
1

Instructions to use Ruzarh/c0ldv_T2V_Sigmoid_Flow_Rank64-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use Ruzarh/c0ldv_T2V_Sigmoid_Flow_Rank64-lora with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    from diffusers.utils import export_to_video
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("ai-toolkit/Wan2.2-T2V-A14B-Diffusers-bf16", dtype=torch.bfloat16, device_map="cuda")
    pipe.load_lora_weights("Ruzarh/c0ldv_T2V_Sigmoid_Flow_Rank64-lora")
    
    prompt = "c0ldv"
    
    output = pipe(prompt=prompt).frames[0]
    export_to_video(output, "output.mp4")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • Draw Things
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Update README.md (Remove Mispleading Info from the Outdated Template)

#1 opened 10 months ago by
qpqpqpqpqpqp
Company
TOS Privacy About Careers
Website
Models Datasets Spaces Pricing Docs